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Machine learning foundations

Track :

Computer Science

Lessons no : 10

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What will you learn in this course?
  • Understand core machine learning concepts including supervised and unsupervised learning techniques
  • Apply linear regression, logistic regression, and neural networks to real-world predictive modeling tasks
  • Perform feature engineering, handle overfitting, and optimize models using gradient descent methods
  • Evaluate model performance using bias-variance tradeoff, accuracy, and other key metrics in machine learning
  • Develop practical skills to build, train, and validate machine learning models for industry applications
  • Gain foundational knowledge to pursue advanced studies or careers in data science and artificial intelligence

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Lessons | 10


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Mahesh Babu Lanka

The course useful
2025-10-23

Shiva

good platform
2025-10-14

Allada Eswari

good
2025-10-13

Shakhawat Hosen

It was decent.
2025-10-08

R.Harish

Good
2025-08-15

daffa tri jayawinata

now i know
2025-07-28

Sajjad Ali Shah

Awesome Site
2025-06-04

Eyerusalem Welay

thank you
2025-06-01

Lerato

i complited the fundamentals of ML and it was an eye openning course, i am interested in deploma course now thanks to mindluster to give me such an information
2025-03-04

VASUNDHRA G

good class
2025-02-04

Mohammad Zaid

...
2025-01-11

Shubham Parsoya

Machine learning foundations
2025-01-10

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Related Courses

Machine learning foundations, in this course is designed to provide a comprehensive introduction to the core concepts and techniques in machine learning. In this course, you will learn the fundamentals of supervised and unsupervised learning, linear regression, logistic regression, and neural networks. Explore key topics such as feature engineering, overfitting, bias-variance tradeoff, and optimization techniques like gradient descent. The course emphasizes practical applications, enabling you to build predictive models and solve real-world problems. With hands-on projects and clear explanations, you’ll gain the foundational knowledge needed to advance in the field of machine learning, preparing you for more advanced studies or industry roles.